1. Field of Use
The present invention relates generally to the field of image recognition. More particularly, the present invention concerns methods and apparatus for recognition of facial images. Specifically, a preferred embodiment of the present invention is directed to a method and apparatus for automatic face recognition by scale, position and rotation (SPR) invariant feature extraction. The present invention thus relates to methods and apparatus for face recognition of the type that can be termed invariant feature extractive.
2. Description of Related Art
Within this application several publications are referenced by arabic numerals in parenthesis. Full citations for these references may be found at the end of the specification immediately preceding the claims. The disclosures of all these references in their entireties are hereby expressly incorporated by reference into the present application for the purposes of indicating the background of the invention and illustrating the state of the art.
An important concern at security facilities is access control. This is a particularly acute problem at highly classified facilities where hundreds of employees must be identified as they enter. Identification (ID) cards are commonly checked by security personnel in such limited access areas. Because of human error, subjectivity, bias and even conspiracy, it would be technically and economically advantageous to automate this process. Indeed, during peak hours an automatic door keeper would reduce frustrating employee lines, as well as problems with stole and lost ID cards. In addition, the installation of several gatekeeping systems inside a limited access facility would permit better protection against intrusion and tighten access to designated areas within the facility.
Accordingly, an automatic face recognition system has long been sought by security agencies, law enforcement agencies, the airline industry, the border patrol, local authorities, and many other organizations. Examples of other potential applicatons are entry control to limited access areas, such as secure facilities in industry, banks, and various private institutions, secure access to computers and video communications, including video telephones, and user verification for automated teller machines (ATM) and credit cards.
The class of techniques that use biological features to classify a person's identity are biometric techniques. Face recognition is such a biometric technique.
Face recognition has an important advantage over other biometric techniques. Face recognition can be both non-invasive and unnoticeable to the subject under investigation. In contrast, fingerprinting and retinal pattern analysis do not share these advantageous features.
Automatic face recognition techniques have a unique place among automatic pattern recognition (APR) technology. Existing APR technology, in general, cannot yet match the performance of a human operator in dealing with a limited number of objects to be classified under varied and frequently noisy conditions. In contrast, APR techniques can deal with a very large number of objects, such as faces, whose classification is beyond the capacity of a human operator simply because of inability to memorize many names and faces, especially after only a single learning exposure.
Heretofore, techniques have been developed in the prior art in an attempt to analyze and identify human faces. For example, an eye blinking method was proposed to recognize individuals by the location, shape and distance between a given set of eyes.sup.(1). The nose, the mouth, and the outline of the face have also been used to identify faces.sup.(1-4). Color image segmentation and the K-L transformation have been used to extract facial features.sup.(5). Neural network classifiers have also been used to perform robust pattern recognition operations.sup.(1,6).
Further, the below-referenced prior patents disclose techniques that were at least in-part satisfactory for the purposes for which they were intended but which had disadvantages. The disclosures of all the below-referenced prior patents in their entireties are hereby expressly incorporated by reference into the present application.
U.S. Pat. Nos. 5,331,544, 5,012,522 and 4,975,960 disclose digitizing data for further processing. U.S. Pat. No. 5,274,714 discloses the use of a frame grabber for digitizing data to be subsequently processed by a neural network. U.S. Pat. Nos. 5,263,097 and 5,255,347 disclose feature extraction for subsequent processing with a neural network.
The above and other techniques, share several common problems. Some of the techniques may take several stages of complex operations to extract features. Some of the techniques require intensive computation which becomes an obstacle to system speed. Many of the recognition techniques are not invariant to position, tilt, and distance and require the individual to place his/her head in a certain position, thus prohibiting the use of such techniques in portal control applications. Many of the techniques require the storage of high resolution face images and/or complex feature vectors in a database. Any one of these disadvantages creates both speed and memory space problems for the use of these techniques in large database applications.